A new coherent processing algorithm for combined subband radar imaging

The problem of radar imagery from multiple sparse frequency subbands initially incoherent to each other is of practical importance for radar target discrimination. In this paper, a new coherent processing technique based on probability density analysis of the subband data is proposed, which is applicable for radar imaging from measurements of two or more initially incoherent radar subbands. The coherence parameters (CPs) for both amplitude and phase are obtained by combining modern spectral analysis with probability density estimation (PDE). The major advantage of the current technique lies in that unlike existent techniques, it enables more robust cohering for the sparse subband data of realworld complex targets.